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分形信号的滤波算法 被引量:2

Filter algorithoms for fractal signals
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摘要 提出了分形信号的小波分解与重构的一种快速算法。针对分形信号的自相似和长时相关的特点,采用离散小波变换(DWT)对分形信号进行多尺度分解,使其成为各尺度上的近似平稳信号,从而可利用通常的Wiener滤波或Kalman滤波方法进行估计,然后再由DWT进行多尺度重构,估计出被噪声污染了的原始信号。重点对DWT的滤波过程进行算法设计,并估计了计算复杂度。 In this paper, a fast algorithm for the fractal signal wavelet decomposition and reconstruction is put foreward. In accordance with the self similar and long-term related characteristics ofthe fractal signals, and by means of discrete wavelet transformation (DWT), multi-scale decompositionis carried out so as to make them become similar stationary signals and estimate them with the usualwiener filtering and Kalman filtering method,Then multi-scale reconstruction is carried out with DWTin order to estimate the primary signals polluted by noises. This paper stresses the algorithm design ofthe DWT filtering process, and the computing complexity is also considered.
出处 《国防科技大学学报》 EI CAS CSCD 1998年第1期103-108,共6页 Journal of National University of Defense Technology
基金 九五国防预研基金 国防科技大学试验技术项目
关键词 分形信号 离散小波变换 滤波算法 信号处理 fractal signal, discrete wavelet transform, Fast Fourier transform, filter
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参考文献5

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  • 2薛东辉,华中理工大学学报,1996年,24卷,8期
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同被引文献15

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